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Abstract:

In cigarette counting applications,a binarization algorithm is needed for the following counting process.But the existing binarization algorithms are   not very effective because cigarettes are small and the areas between cigarettes are also small.In this paper,an improved local maximum entropy average   thresholding method is implemented according to the maximum entropy method presented by Pun.The improved algorithm divides the whole image into areas and selects the optimum threshold for each area according to the maximum entropy threshold and mean.The experimental results prove the validity of the algorithm.

Key words: cigarette counting;maximum entropy;threshold